AI Engineer
Confirmed on the employer's own hiring board on Nov 4, 2026. First seen by Alion on Sep 10, 2026. Altera scores A on the Alion truth index.
Job Details:
Job Description:
AI Engineer - Agentic AI Systems (High-Potential Early Career)
Location: Shanghai, China
Company: Altera
Why This Role Matters
AI is shifting from models to autonomous systems. At Altera, we are building agentic AI platforms tightly coupled with FPGA acceleration, enabling intelligent systems that can reason, act, and scale in real-world environments.
This role is designed for high-potential engineers early in their careers who want to:
work on cutting-edge AI (LLMs + agents + RAG)
gain exposure to hardware-software co-design
and grow quickly into technical leaders in AI systems
What You’ll Work On
Build Real Agentic AI Systems:
Develop LLM-powered agents that use tools, APIs, and data to complete complex tasks
Implement RAG pipelines for large-scale knowledge integration
Ship end-to-end systems from data ingestion → reasoning → action
Go Beyond “Model Usage”
Design multi-step reasoning workflows, not just prompt calls
Evaluate and improve model behavior (accuracy, latency, cost)
Work with both open-source and frontier models
AI Meets Hardware (Differentiator)
Collaborate with FPGA/ASIC teams on hardware-aware AI design
Learn how AI systems are optimized across CPU / GPU / FPGA
Explore efficient inference and system-level performance tradeoffs
Build Platforms, Not Just Features
Develop reusable components for:
memory and context management
tool integration
knowledge retrieval
Contribute to internal AI platforms used across teams
What You’ll Get
Fast Growth
Work directly with senior architects and domain experts
Clear path toward Senior Engineer → Architect roles
High Learning Density
Exposure to both:
modern AI systems (LLMs, agents)
hardware acceleration (FPGA/ASIC)
Real Ownership
Build production systems-not demos
Your work will be used in real engineering workflows
Unique Positioning
Few roles combine:
Agentic AI systems
EDA / semiconductor domain
hardware-aware AI optimization
Qualifications:
What We’re Looking For
Background
Master’s (or exceptional Bachelor’s) in CS, EE, or related field
1-3 years experience (internships, research, or industry)
Technical Strength
Strong coding skills in Python (C++ is a plus)
Hands-on experience building:
AI/ML projects, OR
backend / distributed systems
Solid fundamentals in:
data structures
system design basics
Signal of Excellence (What Sets You Apart)
You’ve built something non-trivial:
AI project, open-source contribution, or research prototype
You learn new frameworks quickly and ship working systems
You’re curious about how systems work end-to-end, not just models
Bonus Points
Experience with:
LangChain, LlamaIndex, or similar
vector databases (FAISS, Milvus, etc.)
Exposure to:
RAG, prompt engineering, or agent workflows
hardware acceleration or performance optimization